In-flight optimal tuning of UAV controllers

Created Date 12/5/2019 晶晶   View Numbers  104 Return    

题目In-flight optimal tuning of UAV controllers
报告人Wojciech Giernacki
内容简介:With an increasing number of multirotor unmanned aerial vehicles (UAVs), solutions supporting the improvement in their precision of operation and safety of autonomous flights are gaining importance. They are particularly crucial in transportation tasks, where control systems are required to provide a stable and controllable flight in various environmental conditions, especially after changing the total mass of the UAV (by adding extra load). In the paper, the problem of using only available basic sensory information for fast, locally best, iterative real-time auto-tuning of parameters of fixed-gain altitude controllers is considered. The machine learning method proposed for this purpose is based on a modified zero-order optimization algorithm (golden-search algorithm) and bootstrapping technique. It has been validated in numerous simulations and real-world experiments in terms of its effectiveness in such aspects as: the impact of environmental disturbances (wind gusts); flight with change in mass; and change of sensory information sources in the auto-tuning procedure. The main advantage of the proposed method is that for the trajectory primitives repeatedly followed by an UAV (for programmed controller gains), the method effectively minimizes the selected performance index (cost function). Such a performance index might, e.g., express indirect requirements about tracking quality and energy expenditure. In the paper, a comprehensive description of the method, as well as a wide discussion of the results obtained from experiments conducted in the AeroLab for a low-cost UAV (Bebop 2), are included. The results have confirmed high efficiency of the method at the expected, low computational complexity.
报告人简介:Wojciech Giernacki was born in Jarocin (Poland) in 1982. He received the M.Sc. degree in control engineering and robotics from the Poznan University of Technology in 2006 and Ph.D. degree in 2011. Since 2011, he is an assistant professor at the Institute of Control, Robotics and Information Engineering of the same university. He founded and heads the PUT AeroLab and Unmanned Aerial Vehicles Research Group (http://uav.put.poznan.pl/). He is an author or co-author of more than 60 publications in peer-reviewed international conferences, articles in impacted journals and 1 book. His scientific interests are focused around the issues of UAVs, especially robust and adaptive control, optimal tuning techniques, as well as data fusion from sensors.

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